Triple
T26845152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Missa Mille Regretz |
E675894
|
entity |
| Predicate | originalChansonLanguage |
P95610
|
FINISHED |
| Object | French |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: French | Statement: [Missa Mille Regretz, originalChansonLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalChansonLanguage Context triple: [Missa Mille Regretz, originalChansonLanguage, French]
-
A.
originalLanguageOfSourceSong
chosen
Indicates that a given language is the original language in which a particular source song was created or first written.
-
B.
originalLanguageOfMelody
Indicates that a specified language is the language in which a particular melody was originally created or first composed.
-
C.
lyricsLanguage
Indicates the language in which the lyrics of a song or musical work are written or performed.
-
D.
languageOfMusic
Indicates that a specified language is used in, associated with, or characteristic of a particular piece of music or musical work.
-
E.
hasOriginalFrenchLyricists
Indicates that an entity (such as a work or song) is associated with the people who wrote its original lyrics in French.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69eee9b8d5e88190a07d3455c0fbb21f |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69fd49f6dbac81909744373a357b7982 |
completed | May 8, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69fd48ed68f481908374183c66a6b055 |
completed | May 8, 2026, 2:22 a.m. |
Created at: April 27, 2026, 5:11 a.m.